Abstract
Alcohol and cigarette consumption have profound effects on genome wide DNA methylation and are common, often cryptic, comorbid features of many psychiatric disorders. This cryptic consumption is a possible impediment to understanding the biology of certain psychiatric disorders because if the effects of substance use are not taken into account, their presence may confound efforts to identify effects of other behavioral disorders. Since the hypothalamic pituitary adrenal (HPA) axis is known to be dysregulated in these disorders, we examined the potential for confounding effects of alcohol and cigarette consumption by examining their effects on peripheral DNA methylation at two key HPA axis genes, NR3C1 and FKBP5.
We found that the influence of alcohol and smoke exposure is more prominent at the FKBP5 gene than the NR3C1 gene. Furthermore, in both genes, loci that were consistently significantly associated with smoking and alcohol consumption demethylated with increasing exposure.
We conclude that epigenetic studies of complex disorders involving the HPA axis need to carefully control for the effects of substance use in order to minimize the possibility of type I and type II errors.
Keywords: DNA methylation, epigenetics, hypothalamic pituitary adrenal axis, psychiatric disorders, smoking, drinking
1. Introduction
One of the largest challenges to the development of an exact understanding of the molecular pathophysiology of individual psychiatric illnesses is that psychiatric disorders are frequently comorbid with one another. For example, according to the National Comorbidity Survey (NCS), subjects with major depression are 3 to 4 times more likely to also have alcohol dependence than those without depression (Kessler et al., 1997). In addition, those with depression are also more likely than most to experience other forms of substance use as well. This high co-morbidity of depression with substance use disorders is not unique. High rates of substance use disorders are found in most anxiety (e.g. panic disorder), psychotic disorders (e.g. schizophrenia) and other mood disorders (e.g. bipolar). Therefore, investigations seeking to isolate molecular signatures for processes associated with non-substance use disorders need to be concerned with the potential effects of co-morbid substance use among their subjects.
This is particularly true for alcohol and tobacco use disorders. Over the past several years, a number of studies have demonstrated the significant effects of cigarette consumption, and more recently alcohol consumption, on genome wide DNA methylation (Breitling et al., 2012; Dogan et al., 2014; Joubert et al., 2012; Monick et al., 2012; Philibert et al., 2014; Zeilinger et al., 2013). In particular, the genes whose methylation patterns are differentially affected by cigarette consumption preferentially map to gene networks implicated in stroke and heart disease (Dogan et al., 2014; Zhang et al., 2014). Furthermore, these and other studies have identified at least two smoke exposure associated epigenetic biomarkers (AHRR and F2RL3) with potential utility for the prevention and treatment of medical illness (Dogan et al., 2014; Philibert et al., 2015; Zhang et al., 2014).
Whether these effects of substance use also map to pathways relevant to the development of other psychiatric disorders is not as well understood. One particular process of interest that could be affected by substance use is the biological response to adversity. Adversity is associated with dysregulation of the hypothalamic pituitary adrenal (HPA) axis and is observed in those with psychiatric disorders including bipolar disorder and depression (Daban et al., 2005; Pariante and Lightman, 2008). Studies have suggested that stress alters DNA methylation at two key HPA axis genes: the glucocorticoid receptor (NR3C1) and its regulator, FK506 binding protein 5 (FKBP5) (Klengel et al., 2013; Non et al., 2012; Oberlander et al., 2008; Perroud et al., 2011).
While most investigators appreciate the need for adjusting the effects of substance use on adversity associated methylation changes, controlling for the exact extent of substance use in research subjects is difficult for at least two reasons. First, due to stigmatization and other adverse outcomes, self-report of smoking and drinking in high risk populations is often unreliable (Burgess et al., 2009; Caraballo et al., 2001; Erim et al., 2007; Russell et al., 2004; Whitford et al., 2009). Second, even if studies utilize biochemical verification of substance use status, current biological measures are known to have limited sensitivity (Florescu et al., 2009; Tavakoli et al., 2011). Hence, should the effects of cigarette or alcohol consumption influence the degree of DNA methylation at a locus of interest for these disorders, both type I and type II errors could arise.
This potential for confounding for genes in the HPA axis is not a theoretical issue. In our recent genome wide study of the effects of heavy alcohol consumption on DNA methylation, we identified a total of 8636 CpG residues whose methylation status were significantly associated with heavy alcohol intake (Philibert et al., 2014). With respect to the 1000 most significant CpG residues, 250 of these probes mapped to intergenic areas while 750 mapped to a total of 653 unique genes. Surprisingly, two genes had five genome wide significant associations mapping to their loci. The first was SLC1A5, a neutral amino acid transporter (Brauers et al., 2005). The second was FKBP5. When these recent results are taken together with our prior understanding of the co-morbidity of alcohol use disorder with psychiatric disorders, they suggest a need to better understand the potential for substance use to confound DNA methylation measurements at commonly studied candidate gene loci.
Therefore, in this communication, we take advantage of recently identified substance use methylation biomarkers and methylation data from three independent cohorts to examine the relationship of alcohol and cigarette consumption to DNA methylation at two key genes in the HPA axis, FKBP5 and NR3C1.
2. Materials and Methods
2.1 Informed consent
The protocols and procedures conducted in each study were approved by their respective Institutional Review Boards. The consent form, procedures, and protocols pertaining to the Family and Community Health Study (FACHS) study were approved by the Institutional Review Board at the University of Iowa, the University of Georgia and Iowa State University (Dogan et al., 2014). The Hannum study was approved by the Institutional Review Boards at the University of San Diego, the University of Southern California and West China Hospital (Hannum et al., 2013). The AlcMeth study was approved by the University of Iowa Institutional Review Board (Philibert et al., 2014).
2.2 Human subjects
The individuals included in this study were from the Family and Community Health Study (FACHS) cohort, an aging study (Hannum) and a study on methylation changes associated with alcohol consumption (AlcMeth). These cohorts have been described in previous studies (Dogan et al., 2014; Hannum et al., 2013; Philibert et al., 2014). The FACHS, Hannum and AlcMeth cohorts consisted of 180, 656 and 64 individuals, respectively. The demographics of these subjects are summarized in Table 1. On average, individuals in the Hannum cohort were over ten years older than those in the FACHS and AlcMeth cohorts.
Table 1.
Demographic and methylation characteristics of subjects from the FACHS, Hannum and AlcMeth cohorts participating in the study
| FACHS | Hannum | AlcMeth | |
|---|---|---|---|
| n | 180 | 656 | 64 |
| Age | 48.9±8.6 | 63.4±14.8 | 46.2±7.8 |
| Gender | |||
| Male | 79 | - | 49 |
| Female | 111 | - | 15 |
| Ethnicity | |||
| Caucasian | 482 | 60 | |
| Hispanic | 174 | 1 | |
| African American | 180 | 3 | |
| Average methylation cg05575921 | 0.749±0.10 | 0.821±0.07 | 0.814±0.13 |
| Average methylation cg23193759 | 0.171±0.03 | 0.167±0.03 | 0.149±0.03 |
2.3 Genome-wide DNA methylation profiling
Peripheral blood mononuclear cell DNA methylation from the FACHS and AlcMeth cohorts and whole blood DNA methylation from the Hannum cohort was profiled using the Illumina (San Diego, CA) Infinium HumanMethylation450 BeadChip. The methylation data of all three cohorts are publically available and can be obtained from the Gene Expression Omnibus (GEO) database: GSE35059 and GSE59550 for FACHS, GSE40279 for Hannum and GSE57853 for AlcMeth. Beta values were derived using the Illumina Genome Studio software.
2.4 Analyses
For all analyses, the methylation at cg05575921 and cg23193759 were used as objective biomarkers to quantify smoking and alcohol consumption, respectively. Cg05575921 is located in intron 3 of the aryl hydrocarbon receptor repressor (AHRR) gene whereas cg23193759 is located on chromosome 10 open reading frame 35. The strong correlation between smoke exposure and methylation changes at cg05575921 is well established and has been consistently replicated (Philibert et al., 2015). While the relationship between alcohol consumption and cg23193759 methylation was only established recently, this locus has been shown to be the most differentially methylated with respect to alcohol use (Philibert et al., 2014). Both loci demethylate with increasing exposure.
There are 41 and 34 CpG sites contained within the Illumina 450K array for the NR3C1 and FKBP5 genes, respectively. Firstly, to determine the influence of smoking (represented by methylation at cg05575921) and alcohol (represented by methylation at cg23193759) on these genes, the average methylation at all loci within each gene was regressed against the biomarkers. Subsequently, to understand if the effects of alcohol and smoking consumption are concentrated at specific regions of the gene, a linear regression model was fitted for each of the 75 loci. Specifically, the methylation of the locus was regressed against each biomarker individually. From all fitted regression models, the regression coefficient, β, the coefficient of determination, R2, and the p-value were extracted. Correction for multiple comparisons was conducted by multiplying each p-value with 75. All analyses were performed in R (Team, 2012).
3. Results
The data for this study was derived from three independent cohorts (Table 1). The first cohort consisted of 180 individuals from the FACHS study (Dogan et al., 2014). The individuals from FACHS who contributed their data are African-American and mostly female (~62%) with an average age in their late 40s. The second cohort is from a study on the epigenetics of aging by Hannum and colleagues (Hannum et al., 2013). These individuals were either Northern European (~73%) or Hispanic (~27%), with an average age in the early 60s. The last cohort (referred to as AlcMeth), consisted of 64 individuals who participated in a commercial case and control study on the epigenetic effects of heavy alcohol consumption (Philibert et al., 2014). These individuals are almost all of Northern European ancestry, mostly male (75%) with their average age being in the mid-40s. Importantly, both the FACHS and the AlcMeth cohorts have high rates of substance use and comorbid medical disorders.
The average DNA methylation for the smoking biomarker, cg05575921, in the FACHS, Hannum and AlcMeth cohorts were 0.749, 0.821, and 0.814, respectively, while the average for the alcohol biomarker, cg23193759, was 0.171, 0.167, and 0.149, respectively (Table 1). As a reference, methylation in lifetime American non-smokers of Northern European ancestry at cg05575921 is approximately 0.91 while the methylation status at the cg23193759 locus in lifetime non-drinkers of Northern European ancestry is approximately 0.17 (Philibert et al., 2015; Philibert et al., 2014).
We examined the influence of cigarette smoking and alcohol consumption on the DNA methylation of the two frequently examined HPA axis genes, FKBP5 and NR3C1. These genes have 34 and 41 Illumina 450k array methylation probes mapping to them, respectively. Details on the placement of the probes, their mean and standard deviations in all three cohorts are provided in Appendix A. The influence of cigarette consumption, as indicated by demethylation at cg05575921, and alcohol consumption, as indicated by demethylation at cg23193759, in the FACHS, Hannum and AlcMeth cohorts were determined by fitting a linear regression model. The results of this analysis are summarized in Tables 2 and 3. The DNA methylation at FKBP5 was significantly associated with smoking and alcohol consumption in all three cohorts, with the most significant smoking and alcohol association observed in the FACHS (p<1.86E-06) and AlcMeth (p<2.16E-07) cohorts, respectively. Similarly, for DNA methylation at NR3C1, a significant association was only observed in the Hannum cohort with respect to alcohol consumption (p<0.0009). This implies that smoking and alcohol has a stronger influence on the DNA methylation of FKBP5 than NR3C1.
Table 2.
Summary of the linear regression parameters in the FACHS, Hannum and AlcMeth cohorts at FKBP5
| Smoking | Alcohol | |
|---|---|---|
| FACHS | ||
| Regression coefficient | 0.058 | 0.145 |
| Percent variation explained by model (%) | 12.03 | 6.86 |
| p-value | 1.85E-06 | 3.81E-04 |
| Hannum | ||
| Regression coefficient | 0.047 | 0.129 |
| Percent variation explained by model (%) | 2.30 | 3.76 |
| p-value | 9.54E-05 | 5.46E-07 |
| AlcMeth | ||
| Regression coefficient | 0.057 | 0.294 |
| Percent variation explained by model (%) | 28.63 | 35.41 |
| p-value | 5.23E-06 | 2.15E-07 |
Table 3.
Summary of the linear regression parameters in the FACHS, Hannum and AlcMeth cohorts at NR3C1
| Smoking | Alcohol | |
|---|---|---|
| FACHS | ||
| Regression coefficient | 0.009 | −0.017 |
| Percent variation explained by model (%) | 0.97 | 0.32 |
| p-value | 0.19 | 0.45 |
| Hannum | ||
| Regression coefficient | 0.017 | 0.064 |
| Percent variation explained by model (%) | 0.52 | 1.68 |
| p-value | 0.06 | 8.76E-04 |
| AlcMeth | ||
| Regression coefficient | 0.009 | −0.001 |
| Percent variation explained by model (%) | 2.88 | 6.75E-06 |
| p-value | 0.18 | 0.98 |
The distribution of substance use induced differential methylation at the generic structural level is still not well understood. To better understand this, we examined the effects of smoking and alcohol consumption at each locus in all three cohorts. The results from this analysis are summarized in Appendices B, C and D for the FACHS, Hannum and AlcMeth cohorts, respectively. In all three cohorts, at the NR3C1 gene, only cg03857453 located in the body of the gene was significantly associated with smoking and drinking. The positive regression coefficient at this locus also suggests that, with increasing levels of smoke exposure and drinking (biomarkers hypomethylation), the methylation level at this locus decreases. While the number of significant associations was larger for FKBP5, the only significant CpG site for smoking common to all three cohorts was cg19226017, located at TSS1500. For alcohol consumption, the only two significant associations observed in all three cohorts were at cg03591753 located at the 5'UTR and cg14284211 located in the body of the gene. Once again, the positive regression coefficients at these loci imply that with increasing exposure, methylation level decreases.
4. Discussion
Examinations of the biology of human behavioral disorders are challenging to conduct for a number of reasons. One of those is the potential for unreliable self-report data (Caraballo et al., 2004; Corbett et al., 2012; Kandel et al., 2006; Webb et al., 2003). The strong effects of substance use on peripheral DNA methylation shown by ourselves and others suggest a potential for the effects of substance use to confound epigenetic analyses. This is particularly true when analyses are not corrected in any way for substance use.
In this study, we investigate the relationship between objective markers of cigarette and alcohol consumption and DNA methylation at two prominent HPA axis genes, FKBP5 and NR3C1, using DNA prepared from blood. The results demonstrate the stronger effects of these substances on the methylation status of the FKBP5 gene and the strong potential for substance use mediated confounding of DNA methylation analyses. The effects of alcohol consumption on FKBP5 methylation are not all that surprising. Prior studies have implicated FKBP5 sequence and expression variation in moderating responses to alcohol use. For example, a recent study by Huang and associates demonstrated that FKBP5 genetic variation moderated the severity of alcohol withdrawal in both humans and rodents (Huang et al., 2014). Using a genome wide approach, Bell and associates showed that acute alcohol intake in rats was associated with increased transcription of FKPB5 (Bell et al., 2009). Consequently, while current findings may have a chilling effect on some biomarker analyses of complex behavioral disorders, when taken together with prior genetic variation and gene expression studies, the current results actually suggest the additional need for further epigenetic and genetic examinations of the role of FKBP5 in moderating alcohol use disorders.
The need to control for substance use effects is probably not limited to studies of the HPA axis. Therefore, the potential for confounding may apply to virtually all epigenetic analyses of psychiatric candidate genes (de Leon and Diaz, 2005; Swendsen et al., 2010). Even so, simply using self-report of alcohol or smoking may not be sufficient to control for the effects of substance use. As compared to the gold standard of cotinine determinations, self-report of smoking is known to be unreliable in some high risk populations (Caraballo et al., 2004; Kandel et al., 2006; Russell et al., 2004). Substance use is not the only variable that needs to be considered as potential confounder in DNA methylation analyses. Age, gender, and body mass index are several variables that are known to have significant effects on genome wide DNA methylation signatures (Almén et al., 2014; Hannum et al., 2013). Fortunately, these variables are generally highly reliably assessed in most data sets. As such, their effects can be readily taken into account. In contrast, the presence or absence of other medical conditions such as type II diabetes, which also has significant genome wide effects (Toperoff et al., 2012), may not always be known, even by the individuals themselves. Hence, some degree of confounding will inevitably be present.
5. Conclusions
In summary, in this communication, we show the broad effects of alcohol and cigarette consumption on DNA methylation at the HPA axis with particularly prominent effects at FKBP5. These results highlight the need for controlling for the effects of substance use in epigenetic studies of complex disorders and the need for further studies on the role of the HPA axis in moderating alcohol use disorders.
Highlights.
Objective DNA methylation biomarkers can quantify smoking and alcohol consumption.
Substance use affects HPA axis DNA methylation.
Influence of substance use is more prominent at FKBP5 than NR3C1.
Acknowledgements
The work in this manuscript was supported by National Institutes of Health grants R01DA037648 to Dr. Robert Philibert and R43AA022041 and R43DA037620 to Behavioral Diagnostics. Additional support for these studies was derived from the Center for Contextual Genetics and Prevention Science (Grant Number P30 DA027827, Dr. Gene Brody) funded by the National Institute on Drug Abuse. This research was supported in part through computational resources provided by The University of Iowa, Iowa City, Iowa. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Role of funding source This study was supported by National Institutes of Health and National Institute on Drug Abuse grants. Funding sources were not involved in the study design, in the collection, analysis and interpretation of data, in writing the report and the decision to submit the article for publication.
Appendices
Appendix A.
The placement of NR3C1 and FKBP5 methylation probes with their respective means and standard deviations in the FACHS, Hannum and AlcMeth cohorts.
| FACHS | Hannum | AlcMeth | |||||||
|---|---|---|---|---|---|---|---|---|---|
| CpG | Gene | Region | Island Status | Mean | Standard Deviation | Mean | Standard Deviation | Mean | Standard Deviation |
| cg12466613 | NR3C1 | TSS1500 | 0.895 | 0.029 | 0.925 | 0.038 | 0.746 | 0.036 | |
| cg07589972 | NR3C1 | TSS1500 | 0.869 | 0.027 | 0.916 | 0.031 | 0.804 | 0.027 | |
| cg26720913 | NR3C1 | 1stExon | 0.015 | 0.007 | 0.019 | 0.012 | 0.019 | 0.011 | |
| cg08818984 | NR3C1 | 1stExon | 0.057 | 0.017 | 0.052 | 0.021 | 0.070 | 0.020 | |
| cg07528216 | NR3C1 | 5'UTR | S_Shelf | 0.918 | 0.018 | 0.944 | 0.022 | 0.865 | 0.019 |
| cg27345592 | NR3C1 | 5'UTR | S_Shore | 0.923 | 0.017 | 0.940 | 0.024 | 0.851 | 0.021 |
| cg13648501 | NR3C1 | 5'UTR | S_Shore | 0.073 | 0.020 | 0.064 | 0.027 | 0.097 | 0.025 |
| cg24026230 | NR3C1 | 5'UTR | S_Shore | 0.025 | 0.008 | 0.016 | 0.007 | 0.024 | 0.009 |
| cg14558428 | NR3C1 | 5'UTR | Island | 0.024 | 0.008 | 0.016 | 0.008 | 0.018 | 0.008 |
| cg21702128 | NR3C1 | TSS1500 | Island | 0.070 | 0.008 | 0.095 | 0.017 | 0.069 | 0.010 |
| cg10847032 | NR3C1 | TSS1500 | Island | 0.042 | 0.008 | 0.053 | 0.010 | 0.048 | 0.012 |
| cg16335926 | NR3C1 | TSS1500 | Island | 0.017 | 0.005 | 0.013 | 0.005 | 0.013 | 0.005 |
| cg18849621 | NR3C1 | TSS1500 | Island | 0.055 | 0.013 | 0.054 | 0.015 | 0.059 | 0.018 |
| cg06968181 | NR3C1 | TSS1500 | Island | 0.063 | 0.028 | 0.026 | 0.015 | 0.028 | 0.014 |
| cg26464411 | NR3C1 | TSS1500 | Island | 0.067 | 0.028 | 0.027 | 0.011 | 0.034 | 0.010 |
| cg18068240 | NR3C1 | 5'UTR | Island | 0.012 | 0.006 | 0.005 | 0.004 | 0.010 | 0.005 |
| cg15645634 | NR3C1 | 5'UTR | Island | 0.028 | 0.008 | 0.017 | 0.006 | 0.025 | 0.007 |
| cg15910486 | NR3C1 | 5'UTR | Island | 0.090 | 0.021 | 0.046 | 0.020 | 0.055 | 0.010 |
| cgO4111177 | NR3C1 | 5'UTR | Island | 0.050 | 0.006 | 0.073 | 0.015 | 0.053 | 0.009 |
| cg17860381 | NR3C1 | 5'UTR | Island | 0.035 | 0.011 | 0.014 | 0.008 | 0.014 | 0.005 |
| cg18019515 | NR3C1 | TSS200 | Island | 0.011 | 0.004 | 0.006 | 0.004 | 0.008 | 0.004 |
| cg11152298 | NR3C1 | TSS200 | Island | 0.062 | 0.006 | 0.080 | 0.011 | 0.064 | 0.009 |
| cg00629244 | NR3C1 | TSS200 | Island | 0.014 | 0.007 | 0.007 | 0.005 | 0.016 | 0.007 |
| cg18146873 | NR3C1 | 1stExon | Island | 0.034 | 0.010 | 0.047 | 0.019 | 0.044 | 0.010 |
| cg20753294 | NR3C1 | 1stExon | Island | 0.062 | 0.020 | 0.039 | 0.028 | 0.055 | 0.018 |
| cg17617527 | NR3C1 | 5'UTR | Island | 0.008 | 0.005 | 0.005 | 0.004 | 0.007 | 0.004 |
| cg06521673 | NR3C1 | 5'UTR | Island | 0.040 | 0.007 | 0.043 | 0.008 | 0.044 | 0.008 |
| cg06952416 | NR3C1 | 5'UTR | N_Shore | 0.068 | 0.027 | 0.041 | 0.027 | 0.074 | 0.032 |
| cg27122725 | NR3C1 | 5'UTR | N_Shore | 0.109 | 0.029 | 0.088 | 0.040 | 0.060 | 0.028 |
| cg18998365 | NR3C1 | 5'UTR | N_Shore | 0.551 | 0.039 | 0.580 | 0.053 | 0.533 | 0.040 |
| cg07733851 | NR3C1 | 5'UTR | N_Shore | 0.320 | 0.039 | 0.354 | 0.057 | 0.344 | 0.037 |
| cg08845721 | NR3C1 | 5'UTR | N_Shore | 0.827 | 0.041 | 0.891 | 0.033 | 0.794 | 0.031 |
| cg17342132 | NR3C1 | Body | N_Shore | 0.711 | 0.060 | 0.865 | 0.030 | 0.730 | 0.056 |
| cg06613263 | NR3C1 | Body | N_Shelf | 0.794 | 0.044 | 0.846 | 0.041 | 0.749 | 0.043 |
| cg27107893 | NR3C1 | Body | 0.860 | 0.035 | 0.897 | 0.053 | 0.743 | 0.053 | |
| cg25535999 | NR3C1 | Body | 0.852 | 0.024 | 0.890 | 0.027 | 0.800 | 0.023 | |
| cg16586394 | NR3C1 | Body | 0.866 | 0.026 | 0.901 | 0.023 | 0.837 | 0.021 | |
| cg18484679 | NR3C1 | Body | 0.867 | 0.024 | 0.913 | 0.034 | 0.786 | 0.026 | |
| cg03857453 | NR3C1 | Body | 0.754 | 0.051 | 0.700 | 0.051 | 0.757 | 0.049 | |
| cg19457823 | NR3C1 | Body | 0.776 | 0.073 | 0.854 | 0.054 | 0.701 | 0.058 | |
| cg23273257 | NR3C1 | 3'UTR | 0.934 | 0.015 | 0.956 | 0.018 | 0.887 | 0.017 | |
| cg08915438 | FKBP5 | TSS1500 | N_Shore | 0.539 | 0.050 | 0.534 | 0.057 | 0.549 | 0.050 |
| cg19226017 | FKBP5 | TSS1500 | N_Shore | 0.766 | 0.040 | 0.719 | 0.039 | 0.722 | 0.034 |
| cg25114611 | FKBP5 | TSS1500 | S_Shore | 0.304 | 0.034 | 0.326 | 0.038 | 0.296 | 0.037 |
| cg17030679 | FKBP5 | 5'UTR | S_Shore | 0.043 | 0.009 | 0.048 | 0.012 | 0.044 | 0.009 |
| cg07485685 | FKBP5 | 5'UTR | Island | 0.030 | 0.009 | 0.016 | 0.010 | 0.017 | 0.006 |
| cg00610228 | FKBP5 | 5'UTR | Island | 0.056 | 0.007 | 0.091 | 0.024 | 0.060 | 0.008 |
| cg11845071 | FKBP5 | 5'UTR | Island | 0.010 | 0.006 | 0.006 | 0.005 | 0.011 | 0.006 |
| cg06937024 | FKBP5 | 5'UTR | N_Shore | 0.032 | 0.015 | 0.012 | 0.006 | 0.008 | 0.004 |
| cg00052684 | FKBP5 | 5'UTR | N_Shore | 0.393 | 0.062 | 0.470 | 0.056 | 0.338 | 0.071 |
| cg23416081 | FKBP5 | 5'UTR | N_Shelf | 0.313 | 0.060 | 0.188 | 0.058 | 0.334 | 0.080 |
| cg15929276 | FKBP5 | 5'UTR | 0.194 | 0.053 | 0.137 | 0.052 | 0.197 | 0.065 | |
| cg03591753 | FKBP5 | 5'UTR | S_Shelf | 0.547 | 0.068 | 0.472 | 0.048 | 0.587 | 0.065 |
| cg08636224 | FKBP5 | 5'UTR | S_Shore | 0.896 | 0.036 | 0.908 | 0.017 | 0.876 | 0.016 |
| cg00130530 | FKBP5 | 5'UTR | S_Shore | 0.612 | 0.052 | 0.631 | 0.040 | 0.607 | 0.048 |
| cg20813374 | FKBP5 | 5'UTR | S_Shore | 0.411 | 0.049 | 0.404 | 0.040 | 0.399 | 0.046 |
| cg01294490 | FKBP5 | TSS200 | S_Shore | 0.089 | 0.017 | 0.080 | 0.017 | 0.100 | 0.024 |
| cg07843056 | FKBP5 | TSS200 | Island | 0.008 | 0.006 | 0.007 | 0.006 | 0.012 | 0.008 |
| cg16012111 | FKBP5 | TSS200 | Island | 0.058 | 0.010 | 0.075 | 0.017 | 0.063 | 0.011 |
| cg10913456 | FKBP5 | 1stExon | Island | 0.007 | 0.004 | 0.007 | 0.011 | 0.007 | 0.004 |
| cg00140191 | FKBP5 | 5'UTR | Island | 0.045 | 0.014 | 0.025 | 0.013 | 0.028 | 0.010 |
| cg00862770 | FKBP5 | 5'UTR | Island | 0.038 | 0.007 | 0.037 | 0.008 | 0.045 | 0.011 |
| cg03546163 | FKBP5 | 5'UTR | N_Shore | 0.503 | 0.074 | 0.550 | 0.097 | 0.423 | 0.062 |
| cg14642437 | FKBP5 | 5'UTR | N_Shelf | 0.844 | 0.027 | 0.842 | 0.035 | 0.797 | 0.026 |
| cg17085721 | FKBP5 | 5'UTR | 0.856 | 0.025 | 0.907 | 0.020 | 0.844 | 0.025 | |
| cg19014730 | FKBP5 | 5'UTR | 0.651 | 0.050 | 0.726 | 0.055 | 0.579 | 0.050 | |
| cg07061368 | FKBP5 | 5'UTR | 0.813 | 0.045 | 0.880 | 0.042 | 0.729 | 0.045 | |
| cg08586216 | FKBP5 | 5'UTR | 0.916 | 0.012 | 0.938 | 0.014 | 0.903 | 0.014 | |
| cg16052510 | FKBP5 | Body | 0.729 | 0.059 | 0.847 | 0.049 | 0.709 | 0.049 | |
| cg14284211 | FKBP5 | Body | 0.246 | 0.050 | 0.151 | 0.047 | 0.225 | 0.054 | |
| cg07633853 | FKBP5 | Body | 0.159 | 0.037 | 0.109 | 0.050 | 0.185 | 0.044 | |
| cg10300814 | FKBP5 | Body | 0.881 | 0.019 | 0.890 | 0.020 | 0.860 | 0.016 | |
| cg06087101 | FKBP5 | Body | 0.412 | 0.081 | 0.412 | 0.073 | 0.407 | 0.064 | |
| cg02665568 | FKBP5 | Body | 0.865 | 0.027 | 0.891 | 0.032 | 0.800 | 0.025 | |
Appendix B.
The smoking and alcohol consumption associated regression coefficient, percent variation explained and corrected p-value of DNA methylation probes at the NR3C1 and FKBP5 genes in the FACHS cohort.
| Smoking | Alcohol Consumption | ||||||
|---|---|---|---|---|---|---|---|
| CpG | Gene | Regression Coefficient | % Variation Explained | Corrected P-value | Regression Coefficient | % Variation Explained | Corrected P-value |
| cg12466613 | KR3C1 | −0.0293 | 0.89 | 1 | −0.1849 | 3.31 | 1 |
| cg07589972 | KR3C1 | 0.0516 | 3.18 | 1 | −0.121 | 1.63 | 1 |
| cg26720913 | KR3C1 | 0.009 | 1.38 | 1 | 0.0528 | 4.55 | 0.355 |
| cg08818984 | KR3C1 | 0.0127 | 0.5 | 1 | 0.0843 | 2.01 | 1 |
| cg07528216 | KR3C1 | 0.023 | 1.44 | 1 | 0.0692 | 1.21 | 1 |
| cg27345592 | KR3C1 | 0.0007 | 0 | 1 | 0.0819 | 1.87 | 1 |
| cg13648501 | KR3C1 | −0.0274 | 1.76 | 1 | −0.1092 | 2.59 | 1 |
| cg24026230 | KR3C1 | −0.0019 | 0.06 | 1 | −0.0192 | 0.54 | 1 |
| cg14558428 | KR3C1 | −0.0189 | 4.72 | 0.253 | −0.0275 | 0.93 | 1 |
| cg21702128 | KR3C1 | 0.0028 | 0.12 | 1 | 0.0515 | 3.83 | 0.651 |
| cg10847032 | KR3C1 | 0.0145 | 3.25 | 1 | 0.0467 | 3.12 | 1 |
| cg16335926 | KR3C1 | −0.0017 | 0.11 | 1 | −0.0129 | 0.61 | 1 |
| cg18849621 | KR3C1 | 0.0245 | 3.17 | 1 | −0.0191 | 0.18 | 1 |
| cg06968181 | KR3C1 | 0.0312 | 1.14 | 1 | 0.0976 | 1.05 | 1 |
| cg26464411 | KR3C1 | −0.0021 | 0 | 1 | 0.0387 | 0.16 | 1 |
| cg18068240 | KR3C1 | −0.0032 | 0.26 | 1 | −0.0031 | 0.02 | 1 |
| cg15645634 | KR3C1 | −0.0162 | 3.68 | 0.742 | −0.0264 | 0.91 | 1 |
| cg15910486 | KR3C1 | 0.0204 | 0.87 | 1 | 0.0517 | 0.52 | 1 |
| cg04111177 | KR3C1 | 0.0084 | 1.67 | 1 | 0.0309 | 2.1 | 1 |
| cg17860381 | KR3C1 | −0.001 | 0.01 | 1 | −0.0014 | 0 | 1 |
| cg18019515 | NR3C1 | 0.0079 | 2.83 | 1 | 0.0181 | 1.38 | 1 |
| cg11152298 | NR3C1 | 0.0041 | 0.37 | 1 | 0.034 | 2.34 | 1 |
| cg00629244 | NR3C1 | −0.0004 | 0 | 1 | 0.0124 | 0.31 | 1 |
| cg18146873 | NR3C1 | −0.0073 | 0.52 | 1 | −0.0139 | 0.17 | 1 |
| cg20753294 | NR3C1 | −0.0048 | 0.05 | 1 | 0.0811 | 1.38 | 1 |
| cg17617527 | NR3C1 | 0.0057 | 1.32 | 1 | 0.0008 | 0 | 1 |
| cg06521673 | NR3C1 | −0.002 | 0.07 | 1 | 0.0057 | 0.05 | 1 |
| cg06952416 | NR3C1 | 0.0577 | 4.31 | 0.418 | −0.0699 | 0.58 | 1 |
| cg27122725 | NR3C1 | −0.035 | 1.28 | 1 | −0.1145 | 1.31 | 1 |
| cg18998365 | NR3C1 | 0.0826 | 4.03 | 0.517 | 0.1691 | 1.57 | 1 |
| cg07733851 | NR3C1 | 0.1013 | 6.18 | 0.057 | 0.1679 | 1.58 | 1 |
| cg08845721 | NR3C1 | 0.0804 | 3.41 | 0.981 | 0.0615 | 0.19 | 1 |
| cg17342132 | NR3C1 | 0.0096 | 0.02 | 1 | 0.1149 | 0.31 | 1 |
| cg06613263 | NR3C1 | 0.1154 | 6.14 | 0.060 | 0.0001 | 0 | 1 |
| cg27107893 | NR3C1 | 0.0561 | 2.26 | 1 | −0.1607 | 1.73 | 1 |
| cg25535999 | NR3C1 | 0.0375 | 2.26 | 1 | −0.0439 | 0.29 | 1 |
| cg16586394 | NR3C1 | 0.0506 | 3.3 | 1 | −0.2473 | 7.34 | 0.018 |
| cg18484679 | NR3C1 | 0.047 | 3.56 | 0.839 | −0.1255 | 2.36 | 1 |
| cg03857453 | NR3C1 | 0.1665 | 9.45 | 0.002 | 0.6602 | 13.84 | 2.04E-05 |
| cg19457823 | NR3C1 | 0.0608 | 0.63 | 1 | −0.7208 | 8.29 | 0.007 |
| cg23273257 | NR3C1 | 0.0189 | 1.47 | 1 | 0.0764 | 2.25 | 1 |
| cg08915438 | FKBP5 | 0.101 | 3.74 | 0.694 | 0.1853 | 1.17 | 1 |
| cg19226017 | FKBP5 | 0.1163 | 7.47 | 0.015 | 0.1348 | 0.94 | 1 |
| cg25114611 | FKBP5 | 0.1088 | 9.06 | 0.003 | 0.1554 | 1.72 | 1 |
| cg17030679 | FKBP5 | 0.0087 | 0.88 | 1 | 0.0194 | 0.4 | 1 |
| cg07485685 | FKBP5 | 0.0124 | 1.78 | 1 | 0.0132 | 0.19 | 1 |
| cg00610228 | FKBP5 | 0.0147 | 3.61 | 0.795 | 0.0335 | 1.75 | 1 |
| cg11845071 | FKBP5 | 0.0023 | 0.15 | 1 | −0.0055 | 0.08 | 1 |
| cg06937024 | FKBP5 | 0.0078 | 0.25 | 1 | 0.0129 | 0.06 | 1 |
| cg00052684 | FKBP5 | 0.042 | 0.42 | 1 | 0.2289 | 1.15 | 1 |
| cg23416081 | FKBP5 | 0.1262 | 4.04 | 0.513 | 0.5154 | 6.27 | 0.052 |
| cg15929276 | FKBP5 | 0.0464 | 0.69 | 1 | 0.03 | 0.03 | 1 |
| cg03591753 | FKBP5 | 0.1609 | 5.13 | 0.167 | 0.8879 | 14.55 | 9.50E-06 |
| cg08636224 | FKBP5 | 0.0281 | 0.56 | 1 | 0.0626 | 0.26 | 1 |
| cg00130530 | FKBP5 | 0.1664 | 9.33 | 0.002 | −0.1729 | 0.94 | 1 |
| cg20813374 | FKBP5 | 0.1934 | 14.03 | 1.66E-05 | 0.0365 | 0.05 | 1 |
| cg01294490 | FKBP5 | 0.0256 | 1.98 | 1 | 0.0533 | 0.8 | 1 |
| cg07843056 | FKBP5 | 0.01 | 2.33 | 1 | −0.0228 | 0.83 | 1 |
| cg16012111 | FKBP5 | 0.0005 | 0 | 1 | 0.028 | 0.67 | 1 |
| cg10913456 | FKBP5 | −0.0062 | 2.15 | 1 | 0.002 | 0.02 | 1 |
| cg00140191 | FKBP5 | 0.0164 | 1.26 | 1 | 0.0339 | 0.51 | 1 |
| cg00862770 | FKBP5 | −0.007 | 0.81 | 1 | 0.0111 | 0.19 | 1 |
| cg03546163 | FKBP5 | 0.1087 | 1.94 | 1 | 0.5202 | 4.13 | 0.465 |
| cg14642437 | FKBP5 | 0.0589 | 4.19 | 0.438 | 0.3242 | 11.83 | 1.70E-04 |
| cg17085721 | FKBP5 | 0.0208 | 0.62 | 1 | 0.1613 | 3.54 | 0.895 |
| cg19014730 | FKBP5 | 0.0608 | 1.34 | 1 | −0.2119 | 1.51 | 1 |
| cg07061368 | FKBP5 | −0.0093 | 0.04 | 1 | −0.1963 | 1.58 | 1 |
| cg08586216 | FKBP5 | 0.0257 | 4.08 | 0.49 | 0.0995 | 5.68 | 0.096 |
| cg16052510 | FKBP5 | 0.0193 | 0.1 | 1 | 0.1872 | 0.86 | 1 |
| cg14284211 | FKBP5 | 0.1106 | 4.41 | 0.349 | 0.9157 | 28.14 | 1.40E-12 |
| cg07633853 | FKBP5 | 0.0371 | 0.89 | 1 | 0.3157 | 6.02 | 0.07 |
| cg10300814 | FKBP5 | 0.048 | 5.67 | 0.096 | 0.1565 | 5.61 | 0.102 |
| cg06087101 | FKBP5 | 0.1063 | 1.55 | 1 | 0.1201 | 0.18 | 1 |
| cg02665568 | FKBP5 | −0.0018 | 0 | 1 | 0.1054 | 1.26 | 1 |
| cg18726036 | FKBP5 | −0.016 | 2.79 | 1 | −0.0121 | 0.15 | 1 |
Appendix C.
The smoking and alcohol consumption associated regression coefficient, percent variation explained and corrected p-value of DNA methylation probes at the NR3C1 and FKBP5 genes in the Hannum cohort.
| Smoking | Alcohol Consumption | ||||||
|---|---|---|---|---|---|---|---|
| CpG | Gene | Regression Coefficient | % Variation Explained | Corrected P-value | Regression Coefficient | % Variation Explained | Corrected P-value |
| cg12466613 | NR3C1 | −0.0185 | 0.13 | 1 | −0.0315 | 0.08 | 1 |
| cg07589972 | NR3C1 | −0.0091 | 0.05 | 1 | −0.0325 | 0.13 | 1 |
| cg26720913 | NR3C1 | −0.0041 | 0.07 | 1 | 0.0341 | 0.93 | 1 |
| cg08818984 | NR3C1 | 0.0151 | 0.27 | 1 | 0.1141 | 3.24 | 2.87E-04 |
| cg07528216 | NR3C1 | 0.0079 | 0.07 | 1 | 0.0082 | 0.01 | 1 |
| cg27345592 | NR3C1 | −0.0041 | 0.01 | 1 | 0.0546 | 0.56 | 1 |
| cg13648501 | NR3C1 | 0.011 | 0.08 | 1 | 0.105 | 1.64 | 0.078 |
| cg24026230 | NR3C1 | −0.0002 | 0 | 1 | −0.0086 | 0.17 | 1 |
| cg14558428 | NR3C1 | −0.0092 | 0.76 | 1 | 0.0269 | 1.32 | 0.285 |
| cg21702128 | NR3C1 | 0.0165 | 0.5 | 1 | 0.0563 | 1.25 | 0.309 |
| cg10847032 | NR3C1 | −0.0093 | 0.43 | 1 | −0.0187 | 0.37 | 1 |
| cg16335926 | NR3C1 | −0.0015 | 0.05 | 1 | 0.0001 | 0 | 1 |
| cg18849621 | NR3C1 | −0.003 | 0.02 | 1 | −0.0153 | 0.12 | 1 |
| cg06968181 | NR3C1 | −0.0094 | 0.19 | 1 | −0.0301 | 0.34 | 1 |
| cg26464411 | NR3C1 | −0.0064 | 0.17 | 1 | 0.0015 | 0 | 1 |
| cg18068240 | NR3C1 | −0.0017 | 0.11 | 1 | −0.001 | 0.01 | 1 |
| cg15645634 | NR3C1 | −0.0034 | 0.16 | 1 | 0.0026 | 0.02 | 1 |
| cg15910486 | NR3C1 | −0.031 | 1.26 | 0.294 | 0.0238 | 0.16 | 1 |
| cg04111177 | NR3C1 | 0.0013 | 0 | 1 | 0.0425 | 0.89 | 1 |
| cg17860381 | NR3C1 | −0.0012 | 0.01 | 1 | −0.002 | 0.01 | 1 |
| cg18019515 | NR3C1 | −0.0011 | 0.04 | 1 | −0.0031 | 0.06 | 1 |
| cg11152298 | NR3C1 | −0.0118 | 0.6 | 1 | 0.0163 | 0.24 | 1 |
| cg00629244 | NR3C1 | 0 | 0 | 1 | −0.0071 | 0.23 | 1 |
| cg18146873 | NR3C1 | 0.017 | 0.42 | 1 | 0.0542 | 0.92 | 1 |
| cg20753294 | NR3C1 | −0.0059 | 0.02 | 1 | −0.0117 | 0.02 | 1 |
| cg17617527 | NR3C1 | 0.0013 | 0.06 | 1 | 0.0042 | 0.15 | 1 |
| cg06521673 | NR3C1 | 0.0013 | 0.01 | 1 | 0.0121 | 0.26 | 1 |
| cg06952416 | NR3C1 | 0.0044 | 0.01 | 1 | 0.0045 | 0 | 1 |
| cg27122725 | NR3C1 | −0.0019 | 0 | 1 | −0.0138 | 0.01 | 1 |
| cg18998365 | NR3C1 | 0.0636 | 0.75 | 1 | 0.2615 | 2.73 | 0.002 |
| cg07733851 | NR3C1 | 0.0956 | 1.46 | 0.144 | 0.1562 | 0.84 | 1 |
| cg08845721 | NR3C1 | 0.0212 | 0.21 | 1 | −0.0847 | 0.74 | 1 |
| cg17342132 | NR3C1 | −0.0129 | 0.09 | 1 | −0.0463 | 0.26 | 1 |
| cg06613263 | NR3C1 | 0.004 | 0 | 1 | −0.1436 | 1.34 | 0.222 |
| cg27107893 | NR3C1 | 0.0603 | 0.67 | 1 | 0.0667 | 0.18 | 1 |
| cg25535999 | NR3C1 | 0.0259 | 0.49 | 1 | −0.0373 | 0.22 | 1 |
| cg16586394 | NR3C1 | 0.0113 | 0.12 | 1 | −0.0355 | 0.26 | 1 |
| cg18484679 | NR3C1 | 0.0013 | 0 | 1 | 0.0122 | 0.01 | 1 |
| cg03857453 | NR3C1 | 0.1438 | 4.17 | 9.93E-06 | 0.4385 | 8.35 | 3.35E-12 |
| cg19457823 | NR3C1 | −0.0095 | 0.02 | 1 | −0.2218 | 1.9 | 0.030 |
| cg23273257 | NR3C1 | −0.0096 | 0.15 | 1 | 0.0438 | 0.66 | 1 |
| cg08915438 | FKBP5 | 0.1474 | 3.54 | 9.27E-05 | 0.2338 | 1.92 | 0.028 |
| cg19226017 | FKBP5 | 0.0809 | 2.25 | 0.009 | 0.127 | 1.2 | 0.377 |
| cg25114611 | FKBP5 | 0.0532 | 1.01 | 0.746 | 0.2186 | 3.67 | 5.69E-05 |
| cg17030679 | FKBP5 | 0.0015 | 0.01 | 1 | 0.018 | 0.25 | 1 |
| cg07485685 | FKBP5 | −0.0116 | 0.71 | 1 | −0.0043 | 0.02 | 1 |
| cg00610228 | FKBP5 | −0.0071 | 0.04 | 1 | −0.0113 | 0.02 | 1 |
| cg11845071 | FKBP5 | 0.0037 | 0.32 | 1 | 0.0043 | 0.09 | 1 |
| cg06937024 | FKBP5 | −0.0039 | 0.19 | 1 | −0.0071 | 0.14 | 1 |
| cg00052684 | FKBP5 | 0.0646 | 0.7 | 1 | −0.0778 | 0.22 | 1 |
| cg23416081 | FKBP5 | 0.0984 | 1.49 | 0.131 | 0.632 | 13.2 | 4.98E-20 |
| cg15929276 | FKBP5 | 0.0313 | 0.19 | 1 | 0.1445 | 0.87 | 1 |
| cg03591753 | FKBP5 | 0.0923 | 1.95 | 0.025 | 0.4794 | 11.34 | 5.46E-17 |
| cg08636224 | FKBP5 | 0.0225 | 0.96 | 0.918 | 0.0145 | 0.09 | 1 |
| cg00130530 | FKBP5 | 0.1225 | 4.89 | 7.78E-07 | −0.0578 | 0.23 | 1 |
| cg20813374 | FKBP5 | 0.1194 | 4.65 | 1.80E-06 | −0.0145 | 0.01 | 1 |
| cg01294490 | FKBP5 | 0.0064 | 0.07 | 1 | 0.0433 | 0.72 | 1 |
| cg07843056 | FKBP5 | 0.0021 | 0.06 | 1 | 0.0007 | 0 | 1 |
| cg16012111 | FKBP5 | −0.0165 | 0.5 | 1 | −0.01 | 0.04 | 1 |
| cg10913456 | FKBP5 | −0.0169 | 1.34 | 1 | −0.0154 | 0.22 | 1 |
| cg00140191 | FKBP5 | −0.0026 | 0.02 | 1 | −0.0209 | 0.28 | 1 |
| cg00862770 | FKBP5 | 0.0023 | 0.04 | 1 | −0.0003 | 0 | 1 |
| cg03546163 | FKBP5 | 0.2096 | 2.42 | 0.005 | 0.5897 | 4.12 | 1.21E-05 |
| cg14642437 | FKBP5 | 0.0211 | 0.19 | 1 | 0.0954 | 0.85 | 1 |
| cg17085721 | FKBP5 | 0.0164 | 0.37 | 1 | 0.0124 | 0.04 | 1 |
| cg19014730 | FKBP5 | 0.0568 | 0.56 | 1 | 0.0198 | 0.01 | 1 |
| cg07061368 | FKBP5 | −0.0337 | 0.33 | 1 | −0.1549 | 1.5 | 0.127 |
| cg08586216 | FKBP5 | 0.0117 | 0.37 | 1 | −0.0048 | 0.01 | 1 |
| cg16052510 | FKBP5 | 0.0247 | 0.13 | 1 | 0.0886 | 0.37 | 1 |
| cg14284211 | FKBP5 | 0.0988 | 2.29 | 0.007 | 0.4543 | 10.43 | 1.65E-15 |
| cg07633853 | FKBP5 | 0.0459 | 0.43 | 1 | 0.3783 | 6.35 | 5.20E-09 |
| cg10300814 | FKBP5 | 0.0282 | 1.03 | 0.708 | 0.0426 | 0.51 | 1 |
| cg06087101 | FKBP5 | 0.0759 | 0.57 | 1 | 0.0802 | 0.14 | 1 |
| cg02665568 | FKBP5 | −0.0021 | 0 | 1 | −0.003 | 0 | 1 |
| cg18726036 | FKBP5 | 0.0024 | 0.02 | 1 | 0.0073 | 0.04 | 1 |
Appendix D.
The smoking and alcohol consumption associated regression coefficient, percent variation explained and corrected p-value of DNA methylation probes at the NR3C1 and FKBP5 genes in the AlcMeth cohort.
| Smoking | Alcohol Consumption | ||||||
|---|---|---|---|---|---|---|---|
| CpG | Gene | Regression Coefficient | % Variation Explained | Corrected P-value | Regression Coefficient | % Variation Explained | Corrected P-value |
| cg12466613 | NR3C1 | −0.0406 | 2.16 | 1 | 0.0632 | 0.24 | 1 |
| cg07589972 | NR3C1 | −0.0412 | 3.87 | 1 | −0.3280 | 11.24 | 0.507 |
| cg26720913 | NR3C1 | −0.0052 | 0.40 | 1 | 0.0117 | 0.09 | 1 |
| cg08818984 | NR3C1 | 0.0064 | 0.17 | 1 | 0.0347 | 0.23 | 1 |
| cg07528216 | NR3C1 | −0.0062 | 0.18 | 1 | −0.0137 | 0.04 | 1 |
| cg27345592 | NR3C1 | 0.0032 | 0.04 | 1 | 0.0756 | 0.99 | 1 |
| cg13648501 | NR3C1 | 0.0280 | 2.13 | 1 | 0.0771 | 0.74 | 1 |
| cg24026230 | NR3C1 | −0.0025 | 0.13 | 1 | −0.0388 | 1.48 | 1 |
| cg14558428 | NR3C1 | −0.0083 | 1.71 | 1 | 0.0692 | 5.55 | 1 |
| cg21702128 | NR3C1 | 0.0018 | 0.05 | 1 | 0.1088 | 8.82 | 1 |
| cg10847032 | NR3C1 | −0.0229 | 5.73 | 1 | −0.0036 | 0.01 | 1 |
| cg16335926 | NR3C1 | 0.0038 | 1.10 | 1 | −0.0270 | 2.47 | 1 |
| cg18849621 | NR3C1 | 0.0087 | 0.39 | 1 | 0.0724 | 1.25 | 1 |
| cg06968181 | NR3C1 | 0.0173 | 2.52 | 1 | 0.0050 | 0.01 | 1 |
| cg26464411 | NR3C1 | 0.0126 | 2.60 | 1 | 0.0872 | 5.67 | 1 |
| cg18068240 | NR3C1 | 0.0013 | 0.12 | 1 | −0.0184 | 1.03 | 1 |
| cg15645634 | NR3C1 | 0.0064 | 1.56 | 1 | 0.0284 | 1.41 | 1 |
| cg15910486 | NR3C1 | 0.0191 | 5.97 | 1 | −0.0369 | 1.02 | 1 |
| cg04111177 | NR3C1 | 0.0021 | 0.10 | 1 | 0.0838 | 7.49 | 1 |
| cg17860381 | NR3C1 | −0.0018 | 0.22 | 1 | −0.0093 | 0.27 | 1 |
| cg18019515 | NR3C1 | 0.0004 | 0.01 | 1 | 0.0279 | 3.66 | 1 |
| cg11152298 | NR3C1 | 0.0087 | 1.60 | 1 | 0.0867 | 7.32 | 1 |
| cg00629244 | NR3C1 | 0.0040 | 0.57 | 1 | 0.0690 | 7.89 | 1 |
| cg18146873 | NR3C1 | −0.0004 | 0.00 | 1 | 0.0696 | 3.50 | 1 |
| cg20753294 | NR3C1 | 0.0218 | 2.56 | 1 | −0.0757 | 1.42 | 1 |
| cg17617527 | NR3C1 | 0.0050 | 2.33 | 1 | −0.0230 | 2.20 | 1 |
| cg06521673 | NR3C1 | 0.0034 | 0.31 | 1 | 0.0754 | 6.89 | 1 |
| cg06952416 | NR3C1 | 0.0029 | 0.01 | 1 | 0.1002 | 0.76 | 1 |
| cg27122725 | NR3C1 | 0.0410 | 3.60 | 1 | 0.2075 | 4.23 | 1 |
| cg18998365 | NR3C1 | 0.1019 | 11.00 | 0.558 | −0.0451 | 0.10 | 1 |
| cg07733851 | NR3C1 | 0.0118 | 0.17 | 1 | −0.0026 | 0 | 1 |
| cg08845721 | NR3C1 | −0.0681 | 8.39 | 1 | −0.3822 | 12.11 | 0.363 |
| cg17342132 | NR3C1 | −0.1458 | 11.39 | 0.48 | −0.8965 | 19.69 | 0.018 |
| cg06613263 | NR3C1 | −0.0876 | 6.98 | 1 | −0.2386 | 2.37 | 1 |
| cg27107893 | NR3C1 | 0.0620 | 2.11 | 1 | −0.1326 | 0.50 | 1 |
| cg25535999 | NR3C1 | −0.0013 | 0.01 | 1 | −0.0577 | 0.50 | 1 |
| cg16586394 | NR3C1 | −0.0224 | 1.85 | 1 | −0.1861 | 5.84 | 1 |
| cg18484679 | NR3C1 | −0.0367 | 3.25 | 1 | −0.0745 | 0.61 | 1 |
| cg03857453 | NR3C1 | 0.2200 | 33.40 | 4.28E-05 | 0.8831 | 24.64 | 0.002 |
| cg19457823 | NR3C1 | −0.1079 | 5.92 | 1 | −0.3183 | 2.36 | 1 |
| cg23273257 | NR3C1 | −0.0045 | 0.12 | 1 | −0.0841 | 1.92 | 1 |
| cg08915438 | FKBP5 | 0.2007 | 27.75 | 0.001 | 0.8771 | 24.26 | 0.003 |
| cg19226017 | FKBP5 | 0.1634 | 39.96 | 1.59E-06 | 0.5490 | 20.64 | 0.012 |
| cg25114611 | FKBP5 | 0.1618 | 32.63 | 6.19E-05 | 0.7582 | 32.80 | 5.71E-05 |
| cg17030679 | FKBP5 | 0.0038 | 0.29 | 1 | 0.0992 | 9.25 | 1 |
| cg07485685 | FKBP5 | −0.0014 | 0.10 | 1 | −0.0070 | 0.12 | 1 |
| cg00610228 | FKBP5 | 0.0061 | 0.90 | 1 | 0.0736 | 5.95 | 1 |
| cg11845071 | FKBP5 | −0.0034 | 0.44 | 1 | 0.0117 | 0.26 | 1 |
| cg06937024 | FKBP5 | 0.0015 | 0.26 | 1 | 0.0301 | 4.52 | 1 |
| cg00052684 | FKBP5 | 0.0171 | 0.10 | 1 | 1.0074 | 14.90 | 0.134 |
| cg23416081 | FKBP5 | 0.3538 | 33.14 | 4.87E-05 | 1.6091 | 31.38 | 1.11E-04 |
| cg15929276 | FKBP5 | 0.1965 | 15.46 | 0.098 | 0.1888 | 0.65 | 1 |
| cg03591753 | FKBP5 | 0.2667 | 28.59 | 4.00E-04 | 1.1008 | 22.30 | 0.006 |
| cg08636224 | FKBP5 | 0.0353 | 8.18 | 1 | 0.0961 | 2.78 | 1 |
| cg00130530 | FKBP5 | −0.0048 | 0.02 | 1 | 0.2608 | 2.24 | 1 |
| cg20813374 | FKBP5 | 0.0990 | 7.73 | 1 | 0.5843 | 12.33 | 0.334 |
| cg01294490 | FKBP5 | 0.0118 | 0.40 | 1 | 0.3264 | 13.85 | 0.184 |
| cg07843056 | FKBP5 | 0.0021 | 0.12 | 1 | 0.0242 | 0.74 | 1 |
| cg16012111 | FKBP5 | −0.0062 | 0.50 | 1 | 0.0633 | 2.35 | 1 |
| cg10913456 | FKBP5 | 0.0035 | 1.54 | 1 | 0.0143 | 1.24 | 1 |
| cg00140191 | FKBP5 | −0.0040 | 0.25 | 1 | −0.0956 | 6.67 | 1 |
| cg00862770 | FKBP5 | 0.0057 | 0.47 | 1 | 0.0728 | 3.55 | 1 |
| cg03546163 | FKBP5 | 0.1800 | 14.08 | 0.169 | 0.9168 | 16.72 | 0.059 |
| cg14642437 | FKBP5 | 0.0608 | 9.48 | 1 | 0.3563 | 14.90 | 0.122 |
| cg17085721 | FKBP5 | −0.0204 | 1.11 | 1 | −0.1119 | 1.53 | 1 |
| cg19014730 | FKBP5 | −0.0348 | 0.80 | 1 | 0.0732 | 0.16 | 1 |
| cg07061368 | FKBP5 | −0.0869 | 6.22 | 1 | −0.4238 | 6.77 | 1 |
| cg08586216 | FKBP5 | −0.0039 | 0.13 | 1 | −0.0458 | 0.82 | 1 |
| cg16052510 | FKBP5 | 0.0281 | 0.56 | 1 | 0.4122 | 5.55 | 1 |
| cg14284211 | FKBP5 | 0.1913 | 21.58 | 0.008 | 1.2158 | 39.91 | 1.63E-06 |
| cg07633853 | FKBP5 | 0.0511 | 2.39 | 1 | 0.4451 | 8.53 | 1 |
| cg10300814 | FKBP5 | 0.0449 | 13.58 | 0.205 | 0.1495 | 6.90 | 1 |
| cg06087101 | FKBP5 | 0.0778 | 2.48 | 1 | 0.0003 | 0 | 1 |
| cg02665568 | FKBP5 | −0.0118 | 0.37 | 1 | 0.0034 | 0 | 1 |
| cg18726036 | FKBP5 | 0.0157 | 1.71 | 1 | −0.0348 | 0.38 | 1 |
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Authors' contributions All authors were involved in all aspects of the study. This includes design, analysis and interpretation of the data, drafting and revising the manuscript and has read and approved the final version of the manuscript.
Conflict of interest The use of DNA methylation to assess alcohol use status is covered by pending property claims. The use of DNA methylation to assess smoking status is covered by US patent 8,637,652 and other pending claims. Dr. Philibert is a potential royalty recipient on those intellectual right claims. Dr. Philibert is an officer and stockholder of Behavioral Diagnostics (www.bdmethylation.com).
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